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Record W3122979885 · doi:10.29173/alr2574

Terrorist Speech under Bills C-51 and C-59 and the Othman Hamdan Case: The Continued Incoherence of Canada’s Approach

2019· article· en· W3122979885 on OpenAlexaffvenueabout
Kent Roach

Bibliographic record

VenueAlberta Law Review · 2019
Typearticle
Languageen
FieldComputer Science
TopicHate Speech and Cyberbullying Detection
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsTerrorismLawAcquittalSociologyThe InternetBill of rightsPolitical scienceCriminologyHuman rights

Abstract

fetched live from OpenAlex

It is argued that neither the approach taken to terrorist speech in Bill C-51 nor Bill C-59 is satisfactory. A case study of the Othman Hamdan case, including his calls on the Internet for “lone wolves” “swiftly to activate,” is featured, along with the use of immigration law after his acquittal for counselling murder and other crimes. Hamdan’s acquittal suggests that the new Bill C-59 terrorist speech offence and take-down powers based on counselling terrorism offences without specifying a particular terrorism offence may not reach Hamdan’s Internet postings. One coherent response would be to repeal terrorist speech offences while making greater use of court-ordered take-downs of speech on the Internet and programs to counter violent extremism. Another coherent response would be to criminalize the promotion and advocacy of terrorist activities (as opposed to terrorist offences in general in Bill C-51 or terrorism offences without identifying a specific terrorist offence in Bill C-59) and provide for defences designed to protect fundamental freedoms such as those under section 319(3) of the Criminal Code that apply to hate speech. Unfortunately, neither Bill C-51 nor Bill C-59 pursues either of these options. The result is that speech such as Hamdan’s will continue to be subject to the vagaries of take-downs by social media companies and immigration law.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.961
Threshold uncertainty score0.469

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.006
GPT teacher head0.200
Teacher spread0.194 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

Quick stats

Citations0
Published2019
Admission routes3
Has abstractyes

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